test: multiple datasets with multiple datafiles column names

Signed-off-by: Will Johnson <mwjohnson728@gmail.com>

tests/data/test_data_preprocessing_utils.py

@@ -607,6 +607,50 @@ def test_process_dataconfig_multiple_files(data_config_path, list_data_path):
         assert formatted_dataset_field in set(train_set.column_names)
 
 
+@pytest.mark.parametrize(
+    "datafiles, datasetconfigname",
+    [
+        (
+            [
+                [
+                    TWITTER_COMPLAINTS_DATA_INPUT_OUTPUT_PARQUET,
+                    TWITTER_COMPLAINTS_DATA_INPUT_OUTPUT_PARQUET,
+                ],
+                [
+                    TWITTER_COMPLAINTS_DATA_INPUT_OUTPUT_JSON,
+                    TWITTER_COMPLAINTS_DATA_INPUT_OUTPUT_JSON,
+                ],
+                [
+                    TWITTER_COMPLAINTS_DATA_INPUT_OUTPUT_JSONL,
+                    TWITTER_COMPLAINTS_DATA_INPUT_OUTPUT_JSONL,
+                ],
+            ],
+            DATA_CONFIG_MULTIPLE_DATASETS_SAMPLING_YAML,
+        ),
+    ],
+)
+def test_process_dataconfig_multiple_datasets_datafiles(datafiles, datasetconfigname):
+    """Ensure that multiple datasets with multiple files are formatted and validated correctly."""
+    with open(datasetconfigname, "r") as f:
+        yaml_content = yaml.safe_load(f)
+    yaml_content["datasets"][0]["data_paths"] = datafiles[0]
+    yaml_content["datasets"][1]["data_paths"] = datafiles[1]
+    yaml_content["datasets"][2]["data_paths"] = datafiles[2]
+
+    with tempfile.NamedTemporaryFile(
+        "w", delete=False, suffix=".yaml"
+    ) as temp_yaml_file:
+        yaml.dump(yaml_content, temp_yaml_file)
+        temp_yaml_file_path = temp_yaml_file.name
+        data_args = configs.DataArguments(data_config_path=temp_yaml_file_path)
+
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+    (train_set, _, _) = _process_dataconfig_file(data_args, tokenizer)
+    assert isinstance(train_set, Dataset)
+    column_names = set(["input_ids", "attention_mask", "labels"])
+    assert set(train_set.column_names) == column_names
+
+
 @pytest.mark.parametrize(
     "data_config_path, list_data_path",
     [